To extract cosmology from CMB experiments, Galactic and extragalactic
foregrounds need to be removed to high accuracy to reveal the primary
CMB anisotropies. There is a large literature on foreground cleaning
methods which will not be reviewed here. Various techniques have been
applied to the Planck data, and are described in
[1]}, [2]}, [3]} (to which we refer the
reader for details, including references to earlier work). Broadly
speaking, the methods can be divided into two classes: methods such as
Commander [4]}, [5]}, which fit a parametric
model of foreground spectral energy distributions to a set of maps at
different frequencies, and template fitting methods which are based on
linear combinations of pixelised maps (or `needlets' in the multipole domain) at different frequencies
(e.g. ILC, SMICA, SEVEM, NILC)ILC: Internal Linear
Combination [6]}; SMICA: Spectral Matching
Independent Component Analysis [7]}; NILC: Needlet
Internal Linear Combination [8]}; SEVEM: Spectral Estimation Via Expectation Maximisation [9]}, [10]}.. In contrast to these techniques, in the
CamSpec likelihood we remove foregrounds by fitting parametric
foreground models to the power spectra over a range of frequencies.
By using power spectra, it is possible to fit foreground components
such as the cosmic infrared background (CIB) which decorrelate with
frequency (see [11]}). Such foregrounds cannot be
cleaned by conventional map based techniques. In addition, we can make
use of the fact that Galactic dust emission is anisotropic on the sky,
whereas extragalactic foregrounds are isotropically distributed. It is
then straightforward to use power spectra computed on different areas
of sky to separate Galactic dust emission from the CIB (see
[12]}). A further advantage is that a parametric foreground
model is `controllable', in the sense that we can investigate power
spectrum residuals for each frequency combination to assess whether a
physically reasonable foreground model (compatible with external data)
provides an acceptable fit to the measured power spectra.
